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Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation

Soil respiration represents the second largest CO(2) flux from terrestrial ecosystems to the atmosphere, and a small rise could significantly contribute to further increase in atmospheric CO(2). Unfortunately, the extent of this effect cannot be quantified reliably, and the outcomes of experiments d...

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Autores principales: Falconer, Ruth E., Battaia, Guillaume, Schmidt, Sonja, Baveye, Philippe, Chenu, Claire, Otten, Wilfred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4437981/
https://www.ncbi.nlm.nih.gov/pubmed/25992875
http://dx.doi.org/10.1371/journal.pone.0123774
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author Falconer, Ruth E.
Battaia, Guillaume
Schmidt, Sonja
Baveye, Philippe
Chenu, Claire
Otten, Wilfred
author_facet Falconer, Ruth E.
Battaia, Guillaume
Schmidt, Sonja
Baveye, Philippe
Chenu, Claire
Otten, Wilfred
author_sort Falconer, Ruth E.
collection PubMed
description Soil respiration represents the second largest CO(2) flux from terrestrial ecosystems to the atmosphere, and a small rise could significantly contribute to further increase in atmospheric CO(2). Unfortunately, the extent of this effect cannot be quantified reliably, and the outcomes of experiments designed to study soil respiration remain notoriously unpredictable. In this context, the mathematical simulations described in this article suggest that assumptions of linearity and presumed irrelevance of micro-scale heterogeneity, commonly made in quantitative models of microbial growth in subsurface environments and used in carbon stock models, do not appear warranted. Results indicate that microbial growth is non-linear and, at given average nutrient concentrations, strongly dependent on the microscale distribution of both nutrients and microbes. These observations have far-reaching consequences, in terms of both experiments and theory. They indicate that traditional, macroscopic soil measurements are inadequate to predict microbial responses, in particular to rising temperature conditions, and that an explicit account is required of microscale heterogeneity. Furthermore, models should evolve beyond traditional, but overly simplistic, assumptions of linearity of microbial responses to bulk nutrient concentrations. The development of a new generation of models along these lines, and in particular incorporating upscaled information about microscale processes, will undoubtedly be challenging, but appears to be key to understanding the extent to which soil carbon mineralization could further accelerate climate change.
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spelling pubmed-44379812015-05-29 Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation Falconer, Ruth E. Battaia, Guillaume Schmidt, Sonja Baveye, Philippe Chenu, Claire Otten, Wilfred PLoS One Research Article Soil respiration represents the second largest CO(2) flux from terrestrial ecosystems to the atmosphere, and a small rise could significantly contribute to further increase in atmospheric CO(2). Unfortunately, the extent of this effect cannot be quantified reliably, and the outcomes of experiments designed to study soil respiration remain notoriously unpredictable. In this context, the mathematical simulations described in this article suggest that assumptions of linearity and presumed irrelevance of micro-scale heterogeneity, commonly made in quantitative models of microbial growth in subsurface environments and used in carbon stock models, do not appear warranted. Results indicate that microbial growth is non-linear and, at given average nutrient concentrations, strongly dependent on the microscale distribution of both nutrients and microbes. These observations have far-reaching consequences, in terms of both experiments and theory. They indicate that traditional, macroscopic soil measurements are inadequate to predict microbial responses, in particular to rising temperature conditions, and that an explicit account is required of microscale heterogeneity. Furthermore, models should evolve beyond traditional, but overly simplistic, assumptions of linearity of microbial responses to bulk nutrient concentrations. The development of a new generation of models along these lines, and in particular incorporating upscaled information about microscale processes, will undoubtedly be challenging, but appears to be key to understanding the extent to which soil carbon mineralization could further accelerate climate change. Public Library of Science 2015-05-19 /pmc/articles/PMC4437981/ /pubmed/25992875 http://dx.doi.org/10.1371/journal.pone.0123774 Text en © 2015 Falconer et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Falconer, Ruth E.
Battaia, Guillaume
Schmidt, Sonja
Baveye, Philippe
Chenu, Claire
Otten, Wilfred
Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title_full Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title_fullStr Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title_full_unstemmed Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title_short Microscale Heterogeneity Explains Experimental Variability and Non-Linearity in Soil Organic Matter Mineralisation
title_sort microscale heterogeneity explains experimental variability and non-linearity in soil organic matter mineralisation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4437981/
https://www.ncbi.nlm.nih.gov/pubmed/25992875
http://dx.doi.org/10.1371/journal.pone.0123774
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